Water Research X最新文献

The impacts of climate change on hydrology underscore the urgency of understanding watershed hydrological patterns for sustainable water resource management. The conventional physics-based fully distributed hydrological models are limited due to computational demands, particularly in the case of large-scale watersheds. Deep learning (DL) offers a promising solution for handling large datasets and extracting intricate data relationships. Here, we propose a DL modeling framework, incorporating convolutional neural networks (CNNs) to efficiently replicate physics-based model outputs at high spatial resolution. The goal was to estimate groundwater head and surface water depth in the Sabgyo Stream Watershed, South Korea. The model datasets consisted of input variables, including elevation, land cover, soil type, evapotranspiration, rainfall, and initial hydrological conditions. The initial conditions and target data were obtained from the fully distributed hydrological model HydroGeoSphere (HGS), whereas the other inputs were actual measurements in the field. By optimizing the training sample size, input design, CNN structure, and hyperparameters, we found that CNNs with residual architectures (ResNets) yielded superior performance. The optimal DL model reduces computation time by 45 times compared to the HGS model for monthly hydrological estimations over five years (RMSE 2.35 and 0.29 m for groundwater and surface water, respectively). In addition, our DL framework explored the predictive capabilities of hydrological responses to future climate scenarios. Although the proposed model is cost-effective for hydrological simulations, further enhancements are needed to improve the accuracy of long-term predictions. Ultimately, the proposed DL framework has the potential to facilitate decision-making, particularly in large-scale and complex watersheds.

Phosphorus (P) is a finite resource and necessary nutrient for agriculture. Urine contains a higher concentration of P than domestic wastewater, which can be recovered by source separation and treatment (hereafter urine diversion). Commercial and institutional (CI) buildings are a logical location for urine diversion since restrooms account for a substantial fraction of water use and wastewater generation. This study estimated the potential for P recovery from human urine and water savings from reduced flushing in CI buildings, and proposed an approach to identify building types and community layouts that are amenable to implementing urine diversion. The results showed that urine diversion is most advantageous in CI buildings with either high daily occupancy counts or times, such as hospitals, schools, office buildings, and airports. Per occupant P recovery benchmarks were estimated to be between 0.04–0.68 g/cap·d. Per building P recovery rates were estimated to be between 0.002–5.1 kg/d, and per building water savings were estimated to be between 3 and 23 % by volume. Recovered P in the form of phosphate fertilizer and potable water savings could accrue profits and cost reductions that could offset the capital costs of new urine diversion systems within 5 y of operation. Finally, urine diversion systems can be implemented at different levels of decentralization based on community layout and organizational structure, which will require socioeconomic and policy acceptance for wider adoption.

Pathogen reduction for the purpose of human health protection is a critical function provided by water reuse systems. Pathogen reduction performance potential is dependent on a wide range of design and operational parameters. Poor understanding of pathogen reduction performance has important consequences—under treatment can jeopardize human health, while over treatment can lead to unnecessary costs and environmental impacts. Documented pathogen reduction potential of the unit processes that make up water reuse treatment trains is based on a highly dispersed and unstructured literature, creating an impediment to practitioners looking to design, model or simply better understand these systems. This review presents a database of compiled log reduction values (LRVs) and log reduction credits (LRCs) for unit processes capable of providing some level of pathogen reduction, with a focus on processes suitable for onsite non-potable water reuse systems. Where reported, we have also compiled all relevant design and operational factors associated with the LRVs and LRCs. Overall, we compiled over 1100 individual LRV data entries for 31 unit processes, and LRCs for 8 unit processes. Results show very inconsistent reporting of influencing parameters, representing a limitation to the use of some of the data. As a standalone resource, the database (included as Supplemental Information) provides water reuse practitioners with easy access to LRV and LRC data. The database is also part of a longer-term effort to optimize the balance between human health protection, potential environmental impacts and cost of water reuse treatment trains.

Recognising the urgent need to address water scarcity resulting from climate change, there is a growing push to enhance the resilience of water (and related) systems. For instance, policymakers are now urging companies to shift from short-term focused strategies towards long-term approaches to effectively manage water scarcity. This paper utilises a custom-built dynamic multisectoral model to assess the socio-economic impacts at a macro-level of temporary water scarcity. The focus of the analysis is to identify the effects that varying levels of investment foresight may have on economic resilience. Specifically, the model incorporates often overlooked factors such as behavioural and resilience aspects. By considering these key elements, a more comprehensive understanding of the system-wide implications of water scarcity on the broader economy is provided. The analysis shows how firms' foresight, or lack thereof, impacts their response to water scarcity and the subsequent impact on the economy. Sector-specific analyses shed light on the potential negative impacts of water scarcity on sectors like agriculture, food, and electricity production and distribution. Yet, the analysis also reveals that certain sectors can benefit from competitiveness effects, which can mitigate the adverse economic implications of water scarcity. However, it should be noted that these sectors may contribute to a catch-up effect on water use. The policy recommendations arising from this research emphasise the promotion of anticipation and preparedness among firms. It is crucial to prioritise resilience-building measures in all sectors, whether they directly rely on water or not.

The use of powdered activated carbon (PAC) is a common process in advanced wastewater treatment to remove micropollutants. Retention and separation of PAC is essential as PAC loaded with micropollutants should not be released into the environment. Determining the activated carbon (AC) residual in the effluent poses a challenge, as there is currently no on-line measurement method. In this study, the correlation between turbidity, measured by scattered light, and absorption at wavelength of 550 nm (Absorption_{550 nm}), measured by transmitted light, was investigated in relation to the AC residue. Linear correlations for turbidity (R² = 0.95) and Absorption_{550 nm} (R² = 1.00) to AC concentrations were observed in both laboratory and full-scale experiments in a pilot plant where superfine PAC was added prior to Pile Cloth Media Filtration (PCMF). Decreasing the particle size (d₅₀) while maintaining the same AC concentration leads to increased turbidity: Therefore, a fourfold reduction in d₅₀ results in a 2- to 3-fold increase in turbidity, whereas a 30-fold reduction in d₅₀ leads to a 6-to 8-fold increase. Furthermore, the original wastewater turbidity led to a parallel shift in the linear correlation between turbidity and AC. Coagulant doses of up to 400 mg Me³⁺/g AC resulted in a 50% reduction in turbidity. However, higher concentrations from 400 to 1,000 mg Me³⁺/g AC resulted in increased turbidity with only a 30% reduction compared to the initial turbidity. The study also highlights the significance of AC particle size in optical measurements, impacting result accuracy.

This study presents the results of systematic wastewater monitoring of SARS-CoV-2 RNA and basic wastewater parameters from four different wastewater treatment plants (WWTPs) in the Czech Republic over the 2020–2022 epidemic. Two-step reverse-transcription quantitative PCR targeting genes encoding the N and Nsp12 proteins was employed to detect SARS-CoV-2 RNA loading in 420 wastewater samples. The results obtained were used to evaluate the potential of wastewater analysis for describing the epidemiological situation in cities of different sizes and determining temporal differences based on the prevailing SARS-CoV-2 variant. Strong correlations between the number of active and hospitalised COVID‐19 cases in each WWTP catchment area and the concentration of SARS-CoV-2 RNA detected in the wastewater clearly demonstrated the suitability of this wastewater-based epidemiological approach for WWTPs of different sizes and characteristics, despite differences in SARS-CoV-2 variant waves, with some WWTPs showing high predictive potential. This study demonstrated on the data from the Czech Republic that targeted systematic monitoring of wastewater provides sufficiently robust data for surveillance of viral loads in sample populations, and thus contributes to preventing the spread of infection and subsequent introduction of appropriate measures.

High-solid anaerobic digestion (HSAD) reject water, distinguished by elevated levels of chemical oxygen demand (COD), NH₄⁺-N and an imbalanced COD/TIN, presents a significant challenge for treatment through conventional partial nitritation/ anammox (PN/A) process. This study introduced a revised two-stage PN/A process, namely partial nitritation/denitritation-anammox (PN-DN/A) process. Its effectiveness was investigated through both pilot-scale (12 t/d) and full-scale (400 t/d) operations, showcasing stable operation with an impressive total removal rate of over 90 % for total inorganic nitrogen (TIN) and exceeding 60 % for COD. Notably, 30 % of TIN was eliminated through heterotrophic denitritation in partial nitritation-denitritation (PN-DN) stage, while approximately 55 % of TIN removal occurred in the anammox stage with anaerobic ammonium oxidizing bacteria (AnAOB) enrichment (Candidatus Kuenenia, 25.9 % and 26.6 % relative abundance for pilot and full scale). In the PN-DN stage, aerobic-anaerobic alternation promoted organics elimination (around 50 % COD) and balanced nitrogen species. Microbial and metagenomic analysis verified the coupling between autotrophic and heterotrophic denitritation and demonstrated that PN-DN stage acted as a protective buffer for anammox stage. This comprehensive study highlights the PN-DN/A process's efficacy in stably treating HSAD reject water.

A growing number of cities and regions are promoting or mandating on-site treatment and reuse of wastewater, which has resulted in the implementation of several thousand on-site water reuse systems on a global scale. However, there is only limited information on the (microbial) water quality from implemented systems. The focus of this study was on two best-in-class on-site water reuse systems in Bengaluru, India, which typically met the local water quality requirements during monthly compliance testing. This study aimed to (i) assess the microbial quality of the reclaimed water at a high temporal resolution (daily or every 15 min), and (ii) explore whether measurements from commercially available sensors can be used to improve the operation of such systems. The monitoring campaign revealed high variations in microbial water quality, even in these best-in-class systems, rendering the water inadequate for the intended reuse applications (toilet flushing and landscape irrigation). These variations were attributed to two key factors: (1) the low frequency of chlorination, and (2) fluctuations of the chlorine demand of the water, in particular of ammonium concentrations. Such fluctuations are likely inherent to on-site systems, which rely on a low level of process control. The monitoring campaign showed that the microbial water quality was most closely related to oxidation–reduction potential (ORP) and free chlorine sensors. Due to its relatively low cost and low need for maintenance, the ORP emerges as a compelling candidate for automating the chlorination to effectively manage variations in chlorine demand and ensure safe water reuse. Overall, this study underscores the necessity of integrating treatment trains, operation, and monitoring for safe on-site water reuse.

Sound urban water management relies on extensive and reliable monitoring of water infrastructure. As low-cost sensors and networks have become increasingly available for environmental monitoring, urban water researchers and practitioners must consider the benefits and disadvantages of such technologies. In this perspective paper, we highlight six technical and socio-technological considerations for low-cost monitoring technology to reach its full potential in the field of urban water management, including: technical barriers to implementation, complementarity with traditional sensing technologies, low-cost sensor reliability, added value of produced information, opportunities to democratize data collection, and economic and environmental costs of the technology. For each consideration, we present recent experiences from our own work and broader literature and identify future research needs to address current challenges. Our experience supports the strong potential of low-cost monitoring technology, in particular that it promotes extensive and innovative monitoring of urban water infrastructure. Future efforts should focus on more systematic documenting of experiences to lower barriers to designing, implementing, and testing of low-cost sensor networks, and on assessing the economic, social, and environmental costs and benefits of low-cost sensor deployments.

In this study, enhanced pyridine bio-photodegradation with assistance of electricity was achieved. Meanwhile, photoelectron-hole played a vital role in accelerating pyridine biomineralization. The significant separation of photoelectron-hole was achieved with an external electric field, which provided sufficient electron donors and acceptors for pyridine biodegradation. The enhanced electron transport system activity also revealed the full utilization of photoelectron-hole by microbes at semiconductor-microbe interface with assistance of electricity. Microbial community analysis confirmed the enrichment of functional species related to pyridine biodegradation and electron transfer. Microbial function analysis and microbial co-occurrence networks analysis indicated that upregulated functional genes and positive interactions of different species were the important reasons for enhanced pyridine bio-photodegradation with external electric field. A possible mechanism of enhanced pyridine biodegradation was proposed, i.e., more photoelectrons and holes of semiconductors were utilized by microbes to accelerate reduction and oxidation of pyridine with the assistance of electrical stimulation. The excellent performance of the photoelectrical biodegradation system showed a potential alternative for recalcitrant organic wastewater treatment.